Molten iron quantity tracking calculation method and device for steel smelting iron tank, medium and product

Abstract

The invention provides a molten iron quantity tracking calculation method and device for a steel smelting iron ladle, a medium and a product, and relates to the technical field of steel smelting intelligent management and control, and the method comprises the steps that the real-time position and the movement track of the molten iron ladle are recognized through a preset ladle label and a plant area positioning base station; inputting the real-time position, the motion trail and the residence time of the molten iron pipe and the distance relation between the molten iron pipe and specific equipment of a factory into a preset process state intelligent judgment model, and judging the current process state of the molten iron tank; obtaining related weighing data corresponding to the process state through a preset data acquisition mode; and according to the related weighing data, the total weight, the tare weight and the net molten iron amount of the molten iron tank are calculated and updated through a corresponding preset data processing method. The method solves the problem that in the prior art, the process state of the molten iron tank is difficult to recognize, and consequently loss tracking of the molten iron amount is inaccurate.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology in steelmaking, and in particular to a method, device, medium, and product for tracking and calculating the amount of molten iron in a steelmaking ladle. Background Technology

[0002] In the steel smelting production process, the molten iron ladle, as the core equipment for molten iron transfer, storage, and process connection, holds crucial data on the net amount of molten iron it carries, which is essential for scheduling production rhythm, controlling smelting process parameters, and calculating production costs. However, steel plant layouts are complex, and molten iron ladles need to be frequently transferred between multiple areas such as the blast furnace tapping area, the blast furnace mixing furnace, and the converter workshop. Furthermore, they must undergo multiple process steps, including tapping, mixing, adding iron, slag removal, and empty ladle return. Under different process conditions, molten iron exhibits various loss types, such as natural cooling loss, residual loss during adding iron, and loss carried away by slag removal, with significant differences in loss mechanisms and rates.

[0003] However, current technologies for tracking molten iron volume largely rely on single-point weighing data during blast furnace tapping or before converter iron addition, lacking the ability to dynamically identify the entire trajectory and process status of the molten iron ladle. This makes it impossible to accurately determine the specific state of the molten iron ladle, such as whether it is in transit, stationary, or undergoing iron addition operations. Consequently, it becomes difficult to distinguish the sources of molten iron loss at different process stages, and the total loss can only be calculated using the initial and final weighing data, failing to achieve real-time tracking and precise breakdown of losses. Summary of the Invention

[0004] The embodiments of the present invention provide a method, device, medium and product for tracking and calculating the amount of molten iron in a steelmaking ladle, aiming to solve the problem that the existing technology has difficulty in identifying the process state of the molten iron ladle, resulting in inaccurate tracking of the loss of molten iron.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a method for tracking and calculating the amount of molten iron in a steelmaking ladle, comprising the following steps: The real-time location and movement trajectory of the molten iron ladle are identified by pre-set ladle tags and plant positioning base stations. The real-time location, trajectory, dwell time, and distance relationship between the molten iron pipe and specific equipment in the factory are input into a predetermined intelligent process status determination model to determine the current process status of the molten iron ladle. The relevant weighing data corresponding to the process state is obtained through a predetermined data acquisition method; Based on the relevant weighing data, the total weight of the molten iron ladle, the tare weight of the molten iron ladle, and the net amount of molten iron are calculated and updated using a corresponding predetermined data processing method.

[0006] Furthermore, the onboard tag is a UWB tag with an integrated IMU inertial measurement unit and / or an RFID tag.

[0007] Furthermore, the data acquisition methods include industrial bus, equipment PLC interface, machine vision system, laser / radar rangefinder and / or pressure sensor.

[0008] Furthermore, the process states include receiving molten iron at the workstation, folding iron, temporarily storing the three lines, parking in the ladle pit, receiving scrap steel, iron mixing operation, ladle transfer, and / or empty ladle waiting.

[0009] Furthermore, the calculation and updating of the total weight of the molten iron ladle, the tare weight of the molten iron ladle, and the net molten iron quantity through a corresponding predetermined data processing method includes one or more of the following: When the process is to receive molten iron at the station, the total weight of the molten iron ladle and the tare weight of the molten iron ladle before receiving the molten iron are weighed and recorded. After receiving the molten iron, the total weight of the molten iron ladle is updated, and the tare weight of the molten iron ladle is subtracted from the total weight of the molten iron ladle to obtain the net amount of molten iron. When the process is in the process of breaking iron, after breaking iron, the amount of iron broken is subtracted from the latest recorded total weight of the molten iron ladle and net molten iron volume, and the total weight of the molten iron ladle and net molten iron volume are updated. When the process state is temporary storage of three lines, retain the latest recorded total weight of molten iron ladle, tare weight of molten iron ladle, and net molten iron quantity; When the process state is that the ladle is parked in the pit, retain the latest recorded total weight of the molten iron ladle, tare weight of the molten iron ladle, and net molten iron volume; When the process status is receiving scrap steel, the total weight of the molten iron ladle is updated by adding the weight of the received scrap steel to the latest recorded tare weight of the molten iron ladle; the material type is updated from molten iron to scrap steel. When the process is in the iron-adding operation, after iron-adding, retain the tare weight of the molten iron ladle, update the total weight of the molten iron ladle to the latest recorded tare weight of the molten iron ladle, and update the net molten iron quantity to zero. When the process state is ladle transfer, retain the latest recorded total weight of the molten iron ladle, tare weight of the molten iron ladle, and net molten iron volume; When the process status is an empty ladle in standby mode, the tare weight of the molten iron ladle is re-weighed and updated.

[0010] Furthermore, the data is bound to the identity ID of the ladle tag in the order of timestamps to obtain a data chain with timestamp, real-time location, process status, total weight of ladle, tare weight of ladle and net amount of molten iron.

[0011] Furthermore, the system displays the location, process status, and net molten iron volume of the entire plant's molten iron ladles in real time through electronic maps, trend charts, and / or lists, and issues warnings when the data link is broken, there are abnormal losses, and / or the molten iron ladle tare weight is abnormal.

[0012] Furthermore, data anomalies are handled, including signal loss fault tolerance processing, state conflict arbitration processing, and / or manual data entry processing. The signal loss fault tolerance processing specifically involves using a predetermined motion prediction algorithm to predict the motion trajectory and process status based on the last known real-time position, velocity vector, and factory map path of the molten iron ladle when the positioning base station network signal is interrupted, and then performing data interpolation. The state conflict arbitration processing specifically involves stopping data updates and sending a prompt to the monitoring center when sensor data is inconsistent with the process status determination. The manual data entry processing specifically involves manually entering the process status through a human-machine interface when the process status cannot be identified.

[0013] Secondly, the present invention provides a device for tracking and calculating the amount of molten iron in a steelmaking ladle, comprising a memory and a processor. The memory stores at least one program, which is executed by the processor to implement the method for tracking and calculating the amount of molten iron in a steelmaking ladle as described above.

[0014] Thirdly, the present invention provides a computer-readable storage medium storing at least one program, which is executed by a processor to implement the method for tracking and calculating the amount of molten iron in a steelmaking ladle as described above.

[0015] Fourthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method for tracking and calculating the amount of molten iron in a steelmaking ladle as described above.

[0016] The above technical solution has the following technical effects: The invention identifies the real-time location and trajectory of the molten iron ladle using pre-set ladle tags and plant positioning base stations. It inputs the real-time location, trajectory, dwell time, and distance to specific plant equipment into a pre-defined intelligent process status determination model to determine the current process status of the molten iron ladle. Relevant weighing data corresponding to the process status is acquired through a pre-defined data acquisition method. Based on this weighing data, the total weight, tare weight, and net molten iron volume of the molten iron ladle are calculated and updated using a pre-defined data processing method. This invention solves the problem of inaccurate tracking of molten iron loss caused by the difficulty in identifying the process status of the molten iron ladle in existing technologies. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a method for tracking and calculating the amount of molten iron in a steelmaking ladle according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of a molten iron quantity tracking and calculation device for a steelmaking ladle according to an embodiment of the present invention. Detailed Implementation

[0018] To further illustrate the various embodiments, the present invention provides accompanying drawings. These drawings are part of the disclosure of the present invention, primarily used to illustrate the embodiments and to explain the operating principles of the embodiments in conjunction with the relevant descriptions in the specification. With reference to these drawings, those skilled in the art should be able to understand other possible implementations and the advantages of the present invention. Components in the drawings are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0019] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments.

[0020] Example 1: Figure 1 This is a flowchart illustrating a method for tracking and calculating the amount of molten iron in a steelmaking ladle according to an embodiment of the present invention. Figure 1 As shown, the method of this embodiment includes the following steps: The real-time location and movement trajectory of the molten iron ladle are identified by pre-set ladle tags and plant positioning base stations. In one specific implementation, each molten iron ladle is assigned a unique identifier using an onboard tag, including a UWB tag integrating an IMU (Inertial Measurement Unit) and an RFID tag. Continuous and precise positioning of the molten iron ladle is achieved through a network of positioning base stations deployed throughout the plant area.

[0021] The real-time location, trajectory, dwell time of the molten iron pipe, and its distance relationship with specific equipment in the factory, such as cranes, iron bending machines, and scrap steel troughs, are input into a predetermined intelligent process status determination model to determine the current process status of the molten iron ladle. In one specific implementation, by predefining electronic fences for all key workstations, equipment, and paths in the factory area, the real-time location information is matched with the electronic fence rule base, such as real-time location, trajectory, dwell time, and specific equipment in the factory, and combined with temporal logic, the process status of the ladle is automatically determined.

[0022] In one specific implementation, the process states include receiving molten iron at the workstation, folding iron, temporarily storing iron in the three lines, storing iron in the ladle pit, receiving scrap steel, performing iron exchange operations, transferring iron between ladle rooms, and / or empty ladle waiting for service.

[0023] Acquire relevant weighing data corresponding to the process status through a predetermined data acquisition method; In one specific implementation, once the process status is determined, relevant data is collected through various means such as industrial buses (e.g., OPC UA), equipment PLC interfaces, machine vision systems, laser / radar rangefinders, and pressure sensors. For example, when the process status is "folding iron," the data from the iron folding flow meter in the iron folding machine system or the difference in weighing values ​​before and after folding is automatically read; when the process status is "receiving scrap steel," the weighing data of the scrap steel trough can be collected. In another specific implementation, the data can undergo preprocessing such as filtering and compensation at the edge or in the cloud.

[0024] Based on the relevant weighing data, the total weight of the molten iron ladle, the tare weight of the molten iron ladle, and the net molten iron volume are calculated and updated using the corresponding predetermined data processing method.

[0025] In one specific implementation, the system continuously maintains the tare weight (empty ladle weight) and total weight of each molten iron ladle, and calculates it using the formula "Net molten iron quantity = Total weight of molten iron ladle - Tare weight of molten iron ladle".

[0026] In one specific implementation, the calculation and updating of the total weight of the molten iron ladle, the tare weight of the molten iron ladle, and the net molten iron quantity through a corresponding predetermined data processing method includes one or more of the following: When the process is in the station to receive molten iron, weigh and record the total weight of the molten iron ladle and the tare weight of the molten iron ladle before receiving the molten iron. After receiving the molten iron, update the total weight of the molten iron ladle and subtract the tare weight of the molten iron ladle from the total weight of the molten iron ladle to obtain the net amount of molten iron. When the process status is "Iron breaking", after iron breaking, subtract the amount of iron broken from the latest recorded total weight of the molten iron ladle and net molten iron volume respectively, and update the total weight of the molten iron ladle and net molten iron volume. When the process status is temporary storage line 3, retain the latest recorded total weight of molten iron ladle, tare weight of molten iron ladle, and net molten iron quantity; When the process status is that the ladle is parked in the pit, retain the latest recorded total weight of the molten iron ladle, tare weight of the molten iron ladle, and net molten iron volume; When the process status is receiving scrap steel, the total weight of the molten iron ladle is updated by adding the weight of the received scrap steel to the latest recorded tare weight of the molten iron ladle; the material type is updated from molten iron to scrap steel. When the process is in the iron-adding operation, after iron-adding, retain the tare weight of the molten iron ladle, update the total weight of the molten iron ladle to the latest recorded tare weight of the molten iron ladle, and update the net molten iron quantity to zero. When the process involves ladle transfer, retain the latest recorded total weight of the molten iron ladle, tare weight of the molten iron ladle, and net molten iron quantity. When the ladle is in an empty standby state, the tare weight of the molten iron ladle is re-weighed and updated. Through dynamic calibration and maintenance of the tare weight, the system achieves accurate calculation of the net weight of the molten iron, avoiding calculation errors caused by tare weight changes due to factors such as slag adhesion, deformation, and cooling of the ladle, thus improving the accuracy of the data.

[0027] In one specific implementation, the data is also bound to the identity ID of the ladle tag in the order of timestamps to obtain a data chain with timestamp, real-time location, process status, total weight of ladle, tare weight of ladle and net amount of molten iron.

[0028] In one specific implementation, the location, process status, and net molten iron volume of the entire plant's molten iron ladles are displayed in real time on the large screen in the central control room through electronic maps, trend charts, and / or lists. Warnings are issued when the data link is broken, there is abnormal loss, and / or the molten iron ladle tare weight is abnormal.

[0029] In one specific implementation, data anomalies are also handled, including signal loss fault tolerance handling, state conflict arbitration handling, and / or manual data entry handling.

[0030] In one specific implementation, the signal loss fault tolerance processing is as follows: when the positioning base station network experiences a brief signal interruption due to the complex environment of the workshop, the system adopts a prediction algorithm based on a motion prediction model and combined with a high-precision digital map of the factory area and logistics rules. Based on the last known coordinates, velocity vector and path of the molten iron ladle on the factory map, the system calculates the most likely trajectory and state and performs data interpolation. Once the signal is restored, the system immediately corrects and confirms the data.

[0031] In one specific implementation, the state conflict arbitration process is as follows: when there is a brief contradiction between sensor data and state discrimination rules, such as the scale showing a sudden drop in weight but the positioning showing that it is not at the iron-folding station, the system will trigger the conflict arbitration mechanism, record the conflict event, freeze the current data update, increase the data acquisition frequency, and send a prompt to the monitoring center until multiple signal sources reach a consensus again, at which point the data link will be automatically unfrozen and corrected.

[0032] In one specific implementation, manual data entry involves the system providing a simple HMI (Human-Machine Interface) when the process status cannot be identified. This allows authorized personnel to perform one-click status confirmation or manually enter key data such as iron content and tare weight. All manual operations will be recorded and marked throughout the process, distinguishing them from automatically recorded data to ensure the authenticity of data traceability.

[0033] In one specific implementation, an embodiment of intelligent control over the entire process of standard iron conversion and iron exchange in heavy-duty tanks includes the following steps: When the TP-202 molten iron ladle arrived at the factory, the system automatically collected the total weight of 150.23t using an unattended intelligent scale, retrieved its latest calibrated tare weight of 40.12t, calculated the net molten iron volume to be 110.11t, generated the initial state online weighing ladle, and wrote it into the database with a timestamp. Based on a UWB and IMU fusion positioning system, the six-degree-of-freedom motion trajectory of the tank is tracked in real time. When the tank is hoisted into the electronic fence of the No. 1 iron bending station and hovers there for more than 15 seconds, the system determines that it has entered the iron bending station and activates the communication link of the station equipment. Once the tank is in place, the laser ranging and pressure sensing system determine that the tank is successfully positioned. The vision system then identifies that the iron bending chute is in place, and the status transitions to "iron bending in progress," triggering a high-frequency data acquisition mode.

[0034] The system directly connects to the PLC for iron bending via the OPC UA protocol to obtain the cumulative value of the high-precision mass flow meter. After temperature compensation and filtering noise reduction, the net weight of the iron bending is obtained as ΔW = 15.27t. The data is then uploaded to the edge computing node for consistency verification. Dynamic update model startup: Total weight = 150.23t - 15.27t = 134.96t; Net weight = 110.11t - 15.27t = 94.84t. Generate data chain record: "Timestamp T1, Workstation: 1# Iron Folding, Event Code: EVT_IRON_DIVERT, ΔTotal Weight: -15.27t, Total Weight: 134.96t, Net Weight: 94.84t"; The moment the crane lifts the crane, the system determines the displacement based on the change in acceleration, the status changes to "transporting", the path tracking algorithm is activated, and the arrival time at the converter is predicted. Upon arrival at the converter iron-collecting point, the system receives the converter tilt encoder signal and the infrared alignment signal, and determines the start of iron collection, activating the iron-collecting process monitoring.

[0035] Once the iron exchange is complete, the system receives a digital signal indicating completion and performs a data reset: total weight = 40.12t (tare weight), net weight = 0t, status is marked as empty tank standby, and logistics scheduling resources are released.

[0036] In one specific implementation, an example of unplanned temporary storage and dynamic path reconstruction includes the following steps: When the TP-203 heavy tank arrived at the factory, the smart scale collected a total weight of 155.37t, obtained a tare weight of 45.15t from the tare weight database, calculated a net weight of 110.22t, and recorded the heavy tank online. The path planning system instructed it to go to the desulfurization station, but the UWB trajectory showed that it deviated from the main path and entered the electronic fence of the three-line A area; The system detects that the tank has been stationary for more than a threshold, such as 300 seconds, triggering the abnormal status detection process. Combined with the crane's RFID signal, it is determined that the tank is temporarily stored unplanned, and the status is updated to "temporarily stored in Zone A of Line 3". Initiate a conservative data maintenance strategy: Total weight, tare weight, and net weight enter read-only mode, continuously record ambient temperature and dwell time, and generate a heartbeat data packet every 5 minutes: "Time T2, Location: Area A, Status: HOLDING, Total weight: 155.37t, Net weight: 110.22t"; Analyze the reasons for temporary storage, correlate with production plan change logs, and dynamically generate new scheduling instructions; Two hours later, the crane's RFID signal was recaptured, and the state was switched to transportation the instant the tank was lifted. The system unfroze the data, and the weight data retained the values ​​at the time of freezing. Upon arrival at the converter iron-collecting point and completion of the standard iron-collecting operation, the data is reset to tare weight 45.15t (net weight 0t), a temporary event report is generated, and the path planning weights are optimized.

[0037] In one specific implementation, an example of transferring molten iron from a desulfurization station ladle to a transfer ladle includes the following steps: The TP-DS01 molten iron ladle in the desulfurization station (total weight 140.08t, tare weight 40.05t, net weight 100.03t) is in the desulfurization station, and the system continuously monitors its temperature and composition data. The transfer tank TP-ZZ01 (tare weight 42.10t, gross weight 42.10t, net weight 0t) was hoisted into the electronic fence of the desulfurization station's tank exchange operation area; The system uses dual base station positioning and crane attitude sensors to determine that the two tanks have entered the tank exchange ready state and activates the dual-tank collaborative tracking mode. At the start of the iron transfer, the system obtains high-precision weighing sensor data through the desulfurization control system, and after Kalman filtering, the net weight transferred is ΔW = 40.20t. Start the tank-to-tank mass transfer algorithm: Source tank TP-DS01: Total weight = 140.08t - 40.20t = 99.88t; Net weight = 100.03t - 40.20t = 59.83t; Target tank TP-ZZ01: Total weight = 42.10t + 40.20t = 82.30t; Net weight = 0t + 40.20t = 40.20t; Generate a related data chain, record the transfer time, location, operator ID, and transfer amount, and mark it as an inter-tank transfer event, and synchronously update the estimated temperature drop model of the two tanks; The transfer tank TP-ZZ01 enters the heavy tank transportation state, and the system plans the optimal path for it to the designated converter.

[0038] In one specific implementation, an example of data prediction and recovery during a location signal interruption includes the following steps: During transportation, the positioning signal strength of the heavy tank TP-206 (total weight 148.30t, tare weight 43.22t, net weight 105.08t) was lower than the threshold, indicating that it had entered a signal blind zone. The anomaly handling module is activated immediately, recording the last reliable coordinates, velocity vector, and orientation angle; Based on the high-precision map of the plant area and logistics rules, the motion prediction algorithm calculates that the most likely path is "towards converter #3", with an estimated travel time of 125 seconds. The system enters predictive tracking mode, keeping the molten iron volume data frozen. The interface displays the predictive positioning status and flashes a warning. After the signal is restored, the U base station re-acquires the tag signal, and calculates the matching degree between the actual coordinates and the predicted coordinates (if the error is <5 meters), the prediction is deemed valid; The system automatically generates data interpolation records, corrects timestamps, achieves seamless data linking, and removes the warning status; If the actual coordinates deviate from the predicted coordinates by more than 10 meters, the system will trigger a path deviation alarm, freeze data updates, and request manual confirmation of the current location and status to ensure the absolute reliability of the data link.

[0039] Example 2: Figure 2 This is a schematic diagram of the iron quantity tracking and calculation device for a steelmaking ladle according to an embodiment of the present invention, as shown below. Figure 2 As shown, the device includes a processor 201, a memory 202, a bus 203, and a computer program stored in the memory 202 and executable on the processor 201. The processor 201 includes one or more processing cores. The memory 202 is connected to the processor 201 via the bus 203. The memory 202 is used to store program instructions. When the processor executes the computer program, it implements the steps in the above-described method embodiment of Embodiment 1 of the present invention.

[0040] Furthermore, as an executable solution, the iron quantity tracking and calculation device for the molten iron ladle can be a computer unit, which can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer unit may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the above-described computer unit structure is merely an example and does not constitute a limitation on the computer unit. It may include more or fewer components, or combine certain components, or use different components. For example, the computer unit may also include input / output devices, network access devices, buses, etc., and this embodiment of the invention does not limit this.

[0041] Furthermore, as an executable solution, the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor is the control center of the computer unit, connecting various parts of the entire computer unit via various interfaces and lines.

[0042] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the computer unit by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital card (SD card), flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0043] Example 3: The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method described in the embodiments of the present invention.

[0044] If the modules / units integrated in the computer unit are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), and software distribution media, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction.

[0045] Example 4: The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method for tracking and calculating the amount of molten iron in a steelmaking ladle as described above.

[0046] Although the invention has been specifically shown and described in conjunction with preferred embodiments, those skilled in the art should understand that various changes in form and detail may be made to the invention without departing from the spirit and scope of the invention as defined in the appended claims, all of which shall be within the scope of protection of the invention.

Claims

1. A method for tracking and calculating the amount of molten iron in a steelmaking ladle, characterized in that, Includes the following steps: The real-time location and movement trajectory of the molten iron ladle are identified by pre-set ladle tags and plant positioning base stations. The real-time location, trajectory, dwell time, and distance relationship between the molten iron pipe and specific equipment in the factory are input into a predetermined intelligent process status determination model to determine the current process status of the molten iron ladle. The relevant weighing data corresponding to the process state is obtained through a predetermined data acquisition method; Based on the relevant weighing data, the total weight of the molten iron ladle, the tare weight of the molten iron ladle, and the net amount of molten iron are calculated and updated using a corresponding predetermined data processing method.

2. The method for tracking and calculating the amount of molten iron in a steelmaking ladle according to claim 1, characterized in that, The onboard tag is a UWB tag with an integrated IMU inertial measurement unit and / or an RFID tag.

3. The method for tracking and calculating the amount of molten iron in a steelmaking ladle according to claim 1, characterized in that, The process states include receiving molten iron at the workstation, folding iron, temporarily storing iron in the three lines, storing iron in the ladle pit, receiving scrap steel, iron mixing operation, ladle transfer, and / or empty ladle waiting.

4. The method for tracking and calculating the amount of molten iron in a steelmaking ladle according to claim 3, characterized in that, The calculation and updating of the total weight of the molten iron ladle, the tare weight of the molten iron ladle, and the net molten iron volume through a corresponding predetermined data processing method includes one or more of the following: When the process is to receive molten iron at the station, the total weight of the molten iron ladle and the tare weight of the molten iron ladle before receiving the molten iron are weighed and recorded. After receiving the molten iron, the total weight of the molten iron ladle is updated, and the tare weight of the molten iron ladle is subtracted from the total weight of the molten iron ladle to obtain the net amount of molten iron. When the process is in the process of breaking iron, after breaking iron, the amount of iron broken is subtracted from the latest recorded total weight of the molten iron ladle and net molten iron volume, and the total weight of the molten iron ladle and net molten iron volume are updated. When the process state is temporary storage of three lines, retain the latest recorded total weight of molten iron ladle, tare weight of molten iron ladle, and net molten iron quantity; When the process state is that the ladle is parked in the pit, retain the latest recorded total weight of the molten iron ladle, tare weight of the molten iron ladle, and net molten iron volume; When the process status is receiving scrap steel, the total weight of the molten iron ladle is updated by adding the weight of the received scrap steel to the latest recorded tare weight of the molten iron ladle; the material type is updated from molten iron to scrap steel. When the process is in the iron-adding operation, after iron-adding, retain the tare weight of the molten iron ladle, update the total weight of the molten iron ladle to the latest recorded tare weight of the molten iron ladle, and update the net molten iron quantity to zero. When the process state is ladle transfer, retain the latest recorded total weight of the molten iron ladle, tare weight of the molten iron ladle, and net molten iron volume; When the process status is an empty ladle in standby mode, the tare weight of the molten iron ladle is re-weighed and updated.

5. The method for tracking and calculating the amount of molten iron in a steelmaking ladle according to claim 1, characterized in that, The data is also bound to the identity ID of the ladle tag in the order of timestamps to obtain a data chain with timestamp, real-time location, process status, total weight of ladle, tare weight of ladle and net amount of molten iron.

6. The method for tracking and calculating the amount of molten iron in a steelmaking ladle according to claim 1, characterized in that, It also displays the location, process status, and net molten iron volume of the entire plant's molten iron ladles in real time through electronic maps, trend charts, and / or lists, and issues warnings when the data link is broken, there is abnormal loss, and / or the molten iron ladle tare weight is abnormal.

7. The method for tracking and calculating the amount of molten iron in a steelmaking ladle according to claim 1, characterized in that, The system also handles data anomalies, including signal loss fault tolerance, state conflict arbitration, and / or manual data entry. Specifically, when the positioning base station network signal is interrupted, a predetermined motion prediction algorithm is used to predict the motion trajectory and process status based on the last known real-time position, velocity vector, and factory map path of the molten iron ladle, and then data interpolation is performed. Specifically, when sensor data and process status are inconsistent, data updates are stopped, and a prompt is sent to the monitoring center. Specifically, when the process status cannot be identified, it is manually entered through a human-machine interface.

8. A device for tracking and calculating the amount of molten iron in a steelmaking ladle, characterized in that, The system includes a memory and a processor, wherein the memory stores at least one program, which is executed by the processor to implement the method for tracking and calculating the amount of molten iron in a steelmaking ladle as described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The storage medium stores at least one program, which is executed by a processor to implement the method for tracking and calculating the amount of molten iron in a steelmaking ladle as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for tracking and calculating the amount of molten iron in a steelmaking ladle as described in any one of claims 1-7.

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